1. Cross Reference to Related Applications
This application is related to application, Ser. No. 08/985,470, filed on the filing date of this application, entitled AUTOMATIC RECIPE ADJUST AND DOWNLOAD BASED ON PROCESS CONTROL WINDOW and to the application, Ser. No. 08/985,467, filed on the filing date of this application, entitled DISPOSITION TOOL FOR FACTORY PROCESS CONTROL both of which are assigned to the assignee of this application.
2. Field of the Invention
This invention relates generally to the manufacture of high performance integrated circuits on semiconductor devices. More specifically, this invention relates to optimizing the manufacture of high performance integrated circuits on semiconductor devices. Even more specifically, this invention relates to optimizing the manufacture of high performance integrated circuits on semiconductor devices using simulated wafer electrical test data (WET) from current and previous layer data.
3. Discussion of the Related Art
In the typical semiconductor manufacturing facility, many simulation and analysis tools have been implemented to assist the process integration and device development efforts. These simulation and analysis tools, however, are typically employed to provide an indication of general trends. The latent potential of reducing the number of silicon runs and speeding up the process optimization cycle has not been fully achieved. One of the primary reasons the process optimization cycle has not been achieved is that the accuracy of the data obtained cannot be established to the degree necessary to determine the dependability of the simulation systems. The accuracy of the data obtained can only be achieved by a complete and detailed engineering calibration of the simulation system. This calibration, however, demands extensive engineering resources and data from multiple silicon production runs which, in turn, is usually only available at the latter stages of the process development or early production cycles.
In addition, process optimization for a technology that has completed qualification and is ramping-up production could receive great benefit from the extensive embedded device physics contained in advanced complex simulation tools.
Current trends in semiconductor process development include the use of these simulation tools to predict certain wafer electrical tests (WET) device performance characteristics based on a predetermined set of process values. The use of these simulation tools has been very effective. Additionally, optimal performance of current large-scale integrated devices can be predicted by a subset of critical WET performance parameters. These performance criteria include speed, operating temperature, power utilization, and reliability.
Furthermore, current manufacturing technology utilizes in-line statistical evaluation of critical parametric values at most module steps in the overall process flow. These statistical values are used to maintain control of the process, at the particular process module in question, often without regard to previous processing results. Often the goal of manufacturing is to meet not only yield goals, but certain performance goals as well. Currently, to do this it is necessary to force certain values to meet very strict specifications, such as shifting polysilicon gate critical dimensions (CD) or increasing or increasing threshold adjust implant, and hope that other process module variations will not adversely affect performance.
Therefore, what is needed is a method of achieving optimum performance is to have a tool that can provide a process control window or specification for the current module by utilizing the previous process step statistical data as a baseline that is entered into a process simulation tool. Such a process control window would have the potential of being much wider than current specifications due to the previous layer parameters and their effects being precisely known and can be considered dynamic since the process control window can change based on actual previous layer data. The simulation tool would be preset to optimize the process to hit certain critical WET parametrics. Using the previous data baseline, and knowing the WET goals, the simulator tool would then provide direction by providing a process control window for the remaining operations to achieve those goals.